Object recognition in images by human vision and computer vision

Q. Chen; J. Dijkstra; B. Vries, de

Object recognition in images by human vision and computer vision

Q. Chen, J. Dijkstra, B. Vries, de

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

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Abstract

Object recognition plays a major role in human behaviour research in the built environment. Computer based object recognition techniques using images as input are challenging, but not an adequate representation of human vision. This paper reports on the differences in object shape recognition between human vision and computer vision. To this end, we explore an image-based recognition algorithm and a model-based recognition algorithm. Experiments were conducted using these two algorithms given images generated by Radiance lighting simulation software. The results reveal significant differences between human vision and computer vision given various conditions in the testing images and in the testing room.

Original language	English
Title of host publication	Conference proceeding of 10th International Conference on Design & Decision Support Systems in Architecture and Urban Planning
Place of Publication	Eindhoven
Pages	CD-ROM-
Publication status	Published - 2010
Event	10th International Conference on Design and Decision Support Systems, (DDSS2010) - Evoluon, Eindhoven, Netherlands Duration: 19 Jul 2010 → 22 Jul 2010 Conference number: 10

Conference

Conference	10th International Conference on Design and Decision Support Systems, (DDSS2010)
Abbreviated title	DDSS2010
Country/Territory	Netherlands
City	Eindhoven
Period	19/07/10 → 22/07/10
Other	10th International Conference om Design and Decision Support Systems in Architecture and Urban Planning, TU/e Eindhoven, 19-22 July 2010

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@inproceedings{842b15a050414349b0ce764fa163352a,

title = "Object recognition in images by human vision and computer vision",

abstract = "Object recognition plays a major role in human behaviour research in the built environment. Computer based object recognition techniques using images as input are challenging, but not an adequate representation of human vision. This paper reports on the differences in object shape recognition between human vision and computer vision. To this end, we explore an image-based recognition algorithm and a model-based recognition algorithm. Experiments were conducted using these two algorithms given images generated by Radiance lighting simulation software. The results reveal significant differences between human vision and computer vision given various conditions in the testing images and in the testing room.",

author = "Q. Chen and J. Dijkstra and {Vries, de}, B.",

year = "2010",

language = "English",

pages = "CD--ROM--",

booktitle = "Conference proceeding of 10th International Conference on Design & Decision Support Systems in Architecture and Urban Planning",

note = "10th International Conference on Design and Decision Support Systems, (DDSS2010), DDSS2010 ; Conference date: 19-07-2010 Through 22-07-2010",

}

Chen, Q, Dijkstra, J & Vries, de, B 2010, Object recognition in images by human vision and computer vision. in Conference proceeding of 10th International Conference on Design & Decision Support Systems in Architecture and Urban Planning. Eindhoven, pp. CD-ROM-, 10th International Conference on Design and Decision Support Systems, (DDSS2010), Eindhoven, Netherlands, 19/07/10.

TY - GEN

T1 - Object recognition in images by human vision and computer vision

AU - Chen, Q.

AU - Dijkstra, J.

AU - Vries, de, B.

N1 - Conference code: 10

PY - 2010

Y1 - 2010

N2 - Object recognition plays a major role in human behaviour research in the built environment. Computer based object recognition techniques using images as input are challenging, but not an adequate representation of human vision. This paper reports on the differences in object shape recognition between human vision and computer vision. To this end, we explore an image-based recognition algorithm and a model-based recognition algorithm. Experiments were conducted using these two algorithms given images generated by Radiance lighting simulation software. The results reveal significant differences between human vision and computer vision given various conditions in the testing images and in the testing room.

AB - Object recognition plays a major role in human behaviour research in the built environment. Computer based object recognition techniques using images as input are challenging, but not an adequate representation of human vision. This paper reports on the differences in object shape recognition between human vision and computer vision. To this end, we explore an image-based recognition algorithm and a model-based recognition algorithm. Experiments were conducted using these two algorithms given images generated by Radiance lighting simulation software. The results reveal significant differences between human vision and computer vision given various conditions in the testing images and in the testing room.

M3 - Conference contribution

SP - CD-ROM-

BT - Conference proceeding of 10th International Conference on Design & Decision Support Systems in Architecture and Urban Planning

CY - Eindhoven

T2 - 10th International Conference on Design and Decision Support Systems, (DDSS2010)

Y2 - 19 July 2010 through 22 July 2010

ER -

Object recognition in images by human vision and computer vision

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